Timeline for Why is differentiating mechanics and integration art?
Current License: CC BY-SA 3.0
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| Jun 10, 2011 at 17:10 | comment | added | Todd Rowland | VonJD: It is conceivable that another computational system would find integration easier. The second half of my post meant to address the human question. The CA analogy, where differentiation is like a step in a CA, shifts the problem to something easier to visualize. That reversing a CA is harder than computing its evolution is something one can see in the wild evolution of rule 30. One of the adhoc methods of integration is knowing what terms to include, and doing this is similar to reversing a CA, both in the cases where it is easy and where it is hard. | |
| Jun 9, 2011 at 6:51 | comment | added | vonjd | @Todd: When you say: "harder for people" you mean that it is the same complexity both ways for a computer? The only thing that differs is the representation custom made for people which differs in its complexity? I think that only shifts the problem: Why is it that for symbolic differentiation representation is easy and for integration not? | |
| Jun 7, 2011 at 18:09 | history | answered | Todd Rowland | CC BY-SA 3.0 |